Sets bounds and initial values for optim by
extracting potentially given values from SVC_mle_control and
checking them, or calculating them from given data. See Details.
init_bounds_optim(control, p, q, id_obj, med_dist, y_var, OLS_mu)(SVC_mle_control output, i.e. list)
(numeric(1)) Number of fixed effects
(numeric(1)) Number of SVCs
(numeric(2*q+1+q)) Index vector to identify the
arguments of objective function.
(numeric(1)) Median distance between observations
(numeric(1)) Variance of response y
(numeric(p)) Coefficient estimates of ordinary
least squares (OLS).
A list with three entries: lower, init,
and upper.
If values are not provided, then they are set in the following way.
Let \(d\) be the median distance med_dist, let \(s^2_y\) be
the variance of the response y_var, and let \(b_j\) be the OLS
coefficients of the linear model. The computed values are given in the
table below.
| Parameter | Lower bound | Initial Value | Upper Bound |
| Range | \(d/1000\) | \(d/4\) | \(10 d\) |
| Variance | \(0\) | \(s^2_y/(q+1)\) | \(10s^2_y\) |
| Nugget | \(10^{-6}\) | \(s^2_y/(q+1)\) | \(10s^2_y\) |
| Mean \(j\) | -Inf |
\(b_j\) | Inf |